Currently known minimally invasive procedures for diagnosis and treatment of medical conditions use shapeable instruments, such as steerable devices, flexible catheters or more rigid arms or shafts, to approach and address various tissue structures within the body. Hereafter, such devices are referred to as “shapeable” instruments. Such a term can include steerable devices, flexible devices, devices having one or more pre-determined shapes (such as an articulating device that locks into a particular shape). For various reasons, it is highly valuable to be able to determine the 3-dimensional spatial position of portions of such shapeable instruments relative to other structures, such as the operating table, other instruments, or pertinent anatomical tissue structures. Such information can be used for a variety of reasons, including, but not limited to: improve device control; to improve mapping of the region; to adapt control system parameters (whether kinematic and/or solid mechanic parameters); to estimate, plan and/or control reaction forces of the device upon the anatomy; and/or to even monitor the system characteristics for determination of mechanical problems. Alternatively, or in combination, shape information can be useful to simply visualize the tool with respect to the anatomy or other regions whether real or virtual
Conventional systems can be improved by incorporating shape information into the control of the medical device. To better understand such improvements a discussion of the concept of shape might be useful. Most generally, shape can include geometric information about an object without information of location, scale or rotation. While the discussion focuses on the use of robotics to control a shapeable device, the concepts disclosed herein can be applied to any robotic, automated, or machine assisted control of a medical device.
Shape can be important for improved control of shapeable devices. In the field of discrete robotics, joint positions are used extensively to describe relative positions of connected articulating members. In the case of a shapeable instrument being advanced by a robotic or other system, there are effectively infinite joints with multiple degrees of freedom. Instead of just knowing the scalar or vector configuration of a joint, the shape of a shapeable section is needed and must be either inferred or measured.
A machine that controls a shapeable medical device carries force and flexure continuously through sections with some degree of smoothness in one or more path derivatives. The shape of these sections can provide valuable information. However, purely defined shape excludes location, rotation and scaling of a body. Shape as described hereafter generally includes shape with scale. Thus with the shape, the relative position and orientation of any two points on the shape are known. For example, as shown in FIG. 1A, if the shape S of shapeable instrument 1 is known and coordinates are known or assigned for q, relative coordinates and orientation may also be assigned for q′ in the reference frame of q. In other words, knowing the shape allows for all point in the body to be defined relative to a reference frame in the body. To reiterate, the reference frame or point is on the shapeable instrument rather than on the actual robot or controlling device.
Without shape measurement, other information must be used to control a shapeable device. However, such control is subject to error by multiple sources. FIG. 1B shows an example of an overview block diagram of a basic topology used for controlling devices without shape feedback. The left side of the diagram (or the Desired/Master side) describes the desired behavior of the catheter (sometimes also referred to as virtual side). The right side of the diagram (referred to as the real, actual, or slave side) describes the behavior of the actual physical catheter. Both sides provide a description of the catheter into at least three levels: tip position (task space), catheter configuration (configuration or joint space), and tendon displacements (actuator space).
FIG. 1B also illustrates a typical control flow for a basic catheter control. The operator enters a command to designate a desired tip position for the device via some input mechanism (a master input device, computer software, or other user interface, etc.). Next, one or more inverse kinematic algorithms compute a desired catheter configuration in order to achieve the commanded tip position. The inverse kinematic algorithm can be varied depending on the construction of the shapeable device. The desired catheter configuration is then fed to one or more catheter mechanics algorithm to compute the positioning element displacements necessary to achieve the desired catheter configuration. These positioning element commands are then provided to the robots control algorithms (or in some cases actuators in the robot that interface with positioning elements in the shapeable element).
Based upon the applied positioning element displacements, the actual (physical) catheter mechanics including any constraints and obstructions acting on the catheter determine the real configuration or shape that the shapeable device achieves. This is illustrated on the right (slave/actual) side of FIG. 1B. This real catheter configuration/shape determines the real catheter tip position. These kinematic relationships of the physical device are represented in the figure with a forward kinematics block (50). Assuming that the operator is observing the catheter tip through some sort of visualization (fluoro, endoscopy, etc), the operator can then use this visual feedback to make corrections to the commanded tip position. However, this form of feedback is based on the human operator's perception and skill, which vary between individuals not to mention that an individual's perception of the feedback can vary during a procedure or over a number of procedures.
To generate the control inputs, the system must calculate inverse kinematics and translate to configuration space. These mathematical operations are essentially inverted by the physical system in actuating the device, subject to disturbances such as interference with the environment.
In many conventional systems, the catheter (or other shapeable instrument) is controlled in an open-loop manner as shown in FIG. 1C. In this type of open loop control model, the shape configuration command comes in to the beam mechanics, is translated to beam moments and forces, then is translated to tendon tensions given the actuator geometry, and finally into tendon displacement given the entire deformed geometry. However, there are numerous reasons why the assumed motion of the catheter will not match the actual motion of the catheter, one important factor is the presence of unanticipated or unmodeled constraints imposed by the patient's anatomy.
Clearly, the presence of unanticipated or unmodeled portions of the anatomy affects the behavior and therefore kinematics of the shapeable instrument. This affect will often alter any mapping between configuration or shape and task space or endpoint for the instrument. FIG. 1D shows a basic example of this situation. When a section of a shapeable instrument articulates without encountering an obstruction (from “a” to “b”), the tip of the instrument (1) moves along an arc that is now oriented largely vertically. When the instrument (1) encounters an environmental constraint (49), the constraint (49) limits the movement of the tip of the instrument (1) in a tighter arc. In most cases, the controller that issues signals to direct the instrument (1) does not account for the presence of this constraint (49), so any inverse kinematic analysis assumes that the instrument (1) is in the shape depicted in B while in reality is in the altered shape depicted in “c”.
Accordingly, a control system that directs shapeable instruments can command joint configurations that can achieve a desired tip position. However, the presence of modeling inaccuracies and environment interaction causes a differential between the actual position from that intended. A simple tip position can quantify this error, but addressing the source of the error requires the additional information regarding the shapeable instrument. Data defining the actual or real shape of the instrument can provide much of this information.
Conventional technologies such as electromagnetic position sensors, available from providers such as the Biosense Webster division of Johnson & Johnson, Inc., can be utilized to measure 3-dimensional spatial position but may be limited in utility for elongate medical instrument applications due to hardware geometric constraints, electromagnetivity issues, etc.
It is well known that by applying the Bragg equation (wavelength=2*d*sin(theta)) to detect wavelength changes in reflected light, elongation in a diffraction grating pattern positioned longitudinally along a fiber or other elongate structure maybe be determined. Further, with knowledge of thermal expansion properties of fibers or other structures which carry a diffraction grating pattern, temperature readings at the site of the diffraction grating may be calculated.
“Fiberoptic Bragg grating” (“FBG”) sensors or components thereof, available from suppliers such as Luna Innovations, Inc., of Blacksburg, Va., Micron Optics, Inc., of Atlanta, Ga., LxSix Photonics, Inc., of Quebec, Canada, and Ibsen Photonics A/S, of Denmark, have been used in various applications to measure strain in structures such as highway bridges and aircraft wings, and temperatures in structures such as supply cabinets.
The use of such technology in shapeable instruments is disclosed in commonly assigned U.S. patent application Ser. Nos. 11/690,116; 11/176,598; 12/012,795; 12/106,254; and 12/507,727. Such technology is also described in U.S. Provisional application Nos. 60/785,001; 60/788,176; 60/678,097; 60/677,580; 60/600,869; 60/553,029; 60/550,961; 60/644,505. The entirety of each of the above applications is incorporated by reference herein.
There remains a need to apply the information gained by the spatial information or shape and applying this information to produce improved device control or improved modeling when directing a robotic or similar device. There also remains a need to apply such controls to medical procedures and equipment.